Analysis of Google Searches for COVID-19 and its symptoms for predicting disease epidemiology in the United States

Analysis of Google Searches for COVID-19 and its symptoms for predicting disease epidemiology in the United States

Authors

  • Camilla Mattiuzzi Service of Clinical Governance, Provincial Agency for Social and Sanitary Services, Trento, Italy
  • Giuseppe Lippi Section of Clinical Biochemistry, University of Verona, Verona, Italy

Keywords:

coronavirus; coronavirus disease 2019; COVID-19; epidemiology

Abstract

N/A

References

Mukhra R, Krishan K, Kanchan T. Possible modes of transmission of Novel coronavirus SARS-CoV-2: a review. Acta Biomed 2020;91:e2020036.

Rovetta A, Bhagavathula AS. Global Infodemiology of COVID-19: Analysis of Google Web Searches and Instagram Hashtags. J Med Internet Res. 2020 Aug 25;22:e20673.

Kurian SJ, Bhatti AUR, Alvi MA, Ting HH, Storlie C, Wilson PM, et al. Correlations Between COVID-19 Cases and Google Trends Data in the United States: A State-by-State Analysis. Mayo Clin Proc 2020;95:2370-2381.

Argenziano MG, Bruce SL, Slater CL, Tiao JR, Baldwin MR, Barr RG, et al. Characterization and clinical course of 1000 patients with coronavirus disease 2019 in New York: retrospective case series. BMJ 2020;369:m1996.

Yan CH, Faraji F, Prajapati DP, Boone CE, DeConde AS. Association of chemosensory dysfunction and COVID-19 in patients presenting with influenza-like symptoms. Int Forum Allergy Rhinol 2020;10:806-813.

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Published

04-12-2020

Issue

Section

CORRESPONDENCE - SPECIAL COVID19

How to Cite

1.
Analysis of Google Searches for COVID-19 and its symptoms for predicting disease epidemiology in the United States. Acta Biomed [Internet]. 2020 Dec. 4 [cited 2024 May 22];92(1):e2021064. Available from: https://www.mattioli1885journals.com/index.php/actabiomedica/article/view/11070

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